Data-scientific study of Kronecker coefficients

Fuente: arXiv
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Main Author: Lee, Kyu-Hwan
Format: Preprint
Published: 2023
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author Lee, Kyu-Hwan
author_facet Lee, Kyu-Hwan
contents We take a data-scientific approach to study whether Kronecker coefficients are zero or not. Motivated by principal component analysis and kernel methods, we define loadings of partitions and use them to describe a sufficient condition for Kronecker coefficients to be nonzero. The results provide new methods and perspectives for the study of these coefficients.
format Preprint
id arxiv_https___arxiv_org_abs_2310_17906
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Data-scientific study of Kronecker coefficients
Lee, Kyu-Hwan
Representation Theory
Combinatorics
We take a data-scientific approach to study whether Kronecker coefficients are zero or not. Motivated by principal component analysis and kernel methods, we define loadings of partitions and use them to describe a sufficient condition for Kronecker coefficients to be nonzero. The results provide new methods and perspectives for the study of these coefficients.
title Data-scientific study of Kronecker coefficients
topic Representation Theory
Combinatorics
url https://arxiv.org/abs/2310.17906